Putting airport data into motion

A European airport authority built a cloud-native modern data platform on Microsoft Azure and Databricks, unifying operational, passenger, and retail data for near-real-time analytics and AI-driven forecasting. Critical airport operation feeds now meet a sub-2-minute SLA, new locations can be onboarded in under 5 days, and passenger forecasting error has been reduced by 25%.

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Industry

Aviation

Region

Europe

Solution

Modern Data Platform & Real-Time Analytics

About the client

A major airport authority connecting millions of passengers

A state-owned airport authority, the organization manages multiple airports and global retail operations, serving tens of millions of passengers annually. Behind every journey is a complex network of aviation logistics, passenger services, airport operations, and commercial retail, all working at scale. Across this interconnected estate, the organization balances the demands of efficient airport operations with passenger experience and commercial performance.

2 min SLA

For critical near real-time operational feeds

Gave the airport operations teams faster access to current operational data.

5 days

To onboard new locations onto the analytics solution

Enabled rapid expansion of the analytics platform across new locations.

1% variance

In airport footfall forecasting

Provided greater precision for operational planning and resource allocation.

25%

Reduction in passenger forecasting error rate

Improved the accuracy of passenger flow forecasts across the airport estate.

The business challenge

A platform built for a different era, facing the demands of a new one

Airport operations depend on decisions made in minutes; from managing security queues and passenger throughput to deploying resources and tracking retail performance. But the technology and data environment supporting those decisions had been built for a different era.

A legacy data foundation

The on-premise data warehouse was more than 15 years old and lacked the scalability and flexibility required for modern airport operations.

Data trapped in silos

Data was fragmented across airline, airport, and retail systems, preventing a unified view of operations and making timely analysis more difficult.

Analytics that couldn't scale consistently

Without a unified data foundation, it was difficult to forecast accurately or provide consistent analytical capabilities to the teams that needed them.

Where friction was building

Fragmented data, limited visibility

Data spread across airline, airport, and retail systems made it difficult to build a unified view across operational and commercial domains.

Decisions constrained by data latency

Without near-real-time data, teams managing throughput, security queues, and passenger flows lacked the timely information needed for operational decisions.

Forecasting lacked precision

Passenger flow forecasting did not provide the accuracy needed to support resource allocation, scheduling, and capacity planning at scale.

Limited visibility across retail operations

The legacy environment could not provide consistent, timely analytics across a global portfolio of retail outlets.

Manual reporting consumed business time

Manual data preparation and reporting across operations, planning, and retail reduced the time available for higher-value analysis.

Unified cloud-native data lakehouse

A Microsoft Azure Data Lakehouse powered by Databricks brings operational, commercial, and passenger data into a unified data environment.

Near real-time streaming pipelines

Streaming pipelines connect critical airport data—including throughput, security queues, and passenger flows—giving operational teams access to a current view of airport activity.

Domain-oriented data products

Data products organized around operations, retail, and planning enable cross-functional analytics within a governed structure.

Self-service analytics for business teams

Curated dashboards, self-service data marts, and AI-driven forecasts give operations, retail, and planning teams direct access to insights without engineering support for every query.

Power BI Direct Lake Mode

Power BI Direct Lake Mode supports interactive dashboards and predictive analytics with high-performance, low-latency reporting.

Governance and security via Unity Catalog

Unity Catalog provides governance, access control, and security across data domains, supported by centralized logging, auditing, SLA monitoring, and data quality controls.

Ingest–Transform–Serve architecture

Data moves from multiple airport source systems into the lakehouse, through curated transformation layers, and into dashboards and advanced models for near-real-time operational use.

Future-proofed for GenAI and Copilot-era use cases

The platform provides a governed data foundation for advanced forecasting, generative AI, and Copilot-style decision-support use cases.

One data foundation.
One connected view.
Faster airport decisions.

What it enabled

Near real-time operational intelligence

Operations teams now have a live, unified view of throughput, security queues, and passenger flows, enabling faster, more confident decisions across the airport estate.

A single source of truth

For the first time, operational and retail data domains share a common, governed data foundation, eliminating the inconsistencies and reconciliation overhead of a siloed environment.

Accurate passenger forecasting at scale

Sub-1% variance in footfall forecasting and a 25% reduction in forecasting error rate give planning teams the precision they need for resource allocation, scheduling, and capacity management.

Global retail analytics

Performance across international retail outlets is tracked through a unified analytics layer, giving commercial teams the visibility to optimize the retail portfolio at scale.

Empowered business users

Self-service dashboards and data products have shifted analytical capability directly into business teams, reducing dependency on central data engineering resources and accelerating time to insight.

Operational
SLA

Sub-2-minute SLA for critical near-real-time operational feeds.

Manual effort
reduction

Reduced manual reporting and data preparation across operations, retail, and planning teams.

Platform scalability

New locations onboarded to the analytics solution in under five days.

Decision-making speed

Near-real-time operational data gives teams faster access to the information needed for airport decision-making.

Forecasting
precision

Less than 1% variance in airport footfall forecasting.

Unified data
estate

A single source of truth across operational and retail data domains replaced fragmented, siloed systems.

Forecast accuracy
improvement

25% reduction in passenger forecasting error rate.

Cloud data platform

Microsoft Azure as the foundational cloud environment, with secure on-premises connectivity via ExpressRoute.

Unified data engineering and ML/AI

Databricks for ETL processing, machine learning, and AI workloads — providing a single compute environment for both engineering and data science.

Storage and architecture

Azure Data Lakehouse with a cloud-native Lakehouse architecture following an Ingest–Transform–Serve model.

Visualization and reporting

Power BI with Direct Lake Mode for interactive, high-performance dashboards and predictive analytics.

Governance and security

Unity Catalog for enterprise data governance, access control, and security across all data domains.

Streaming and real-time processing

Near real-time streaming pipelines for critical airport operational systems.

Operational frameworks

Latency and SLA monitoring framework, centralized logging and auditing framework, and a data quality framework across all domains.

Integration approach

Low-code/no-code integration patterns enabling rapid onboarding of new data sources and locations.

From legacy constraint to modern capability

A 15-year-old on-premise data warehouse was replaced with a cloud-native data foundation designed to scale as operational and analytical needs evolve.

From siloed data to unified intelligence

Operational, passenger, and retail data now come together through a single, governed platform, creating a consistent foundation for analytics across the organization.

From reactive to real-time operations

Near-real-time streaming gives operational teams more timely visibility into throughput, security queues, and passenger flows.

From centralized reporting to self-service insight

Curated data products, dashboards, and self-service analytics give operations, retail, and planning teams more direct access to the data and insights they need.

Built for advanced AI

A governed data foundation supports advanced forecasting and provides the foundation for future generative AI and Copilot-style decision-support use cases.

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